Clothes brand sees 141% increase in revenue per campaign

Clothing retailer Johnny Cupcakes had an email list of 80,000 customers, however the data was incomplete and everyone received the same marketing messages.

In order to make its emails more effective, Johnny Cupcakes initially used vendor software to mine additional information from its customers’ social profiles.

It was then able to find out data on gender, customer interests, brand preferences and media habits.

For the first time the business could then run a product launch campaign with separate emails for men and women who had expressed an interest in baseball.

This fairly simple segmentation resulted in:

  • 42% increase in clickthrough rates.
  • 123% increase in conversion rate.
  • 141% increase in revenue per campaign.

Pet retailer boosts CTR by 750%

Flash sale site Doggyloot segments and personalises its emails based on the type of dog that its customers own, so people with big dogs get different emails to those who own a terrier.

In order to collect this information the company offered incentives to its existing email list if they shared their dog’s size and birthday.

The campaigns are now segmented into three groups based on dog size, and yield good results:

  • Open rate up 10.2%.
  • Clickthrough rate is 410% higher than average.
  • Contributes up to 13% of daily total revenue.

Doggyloot also triggers emails to wish dogs a happy birthday. A few results of that email include:

  • Open rate up 28.1%.
  • Clickthrough rate is 750% higher than the team’s average.
  • Contributes up to 16% of daily total revenue.

Fashion store increases sales by 5.5x

In this case study an unnamed fashion store managed to increase purchase conversion by 5.5x using email segmentation.

It targeted customers who had made a big one-off purchase then not returned to the site for several months, which accounted for about 12% of its user base.

The fashion store targeted these people with a campaign that thanked them for their previous purchase and offered them a small incentive to buy something else.

A week after running the campaign the company measured the results against the directly previous email campaign. The open rate and click rate were both 1.4x higher, but the conversion rate was a massive 5.5x higher.

The average basket size was also larger than normal, so on a dollar-per-email basis the campaign yielded 15.7x higher sales.

Weekly newsletter achieves 400% lift in reactivation of inactive subscribers

Gig and ticketing site Eventful kicked its segmentation up a notch by personalising emails based on artists that the customers had interacted with on its site.

An algorithm also allowed Eventful to suggest other artists that people may be interested in based on their previous activity.

These personalised recommendations were built into its existing email newsletter, The Weekly Entertainment Guide, and also formed the basis of a new email product, Recommended Performer Alerts.

Eventful recommends men in cowboy hats:

Eventful used this new recommendation engine as a way of appealing to lapsed subscribers and achieved a 400% increase in reactivation rates.

Other results for the Weekly Events Guide included:

  • 26% open rate increase.
  • 97% clickthrough increase.
  • 56% increase in click-to-open rate.

While for the Recommended Performer Alert:

  • 15% median open rate.
  • 3% median click rate.

Air New Zealand’s personalised travel emails

Air New Zealand built a personalised email campaign that was aimed at building customer loyalty by improving the passenger experience. 

The campaign is known as ‘Personality Allowed’ and involved sending personalised pre-flight and post-arrival emails to passengers.

Pre-flight emails include imagery of the upcoming destination, a weather update, and flight details. Each each message also introduces a flight crew member who will be on the recipient’s specific flight.

The post-arrival emails include a link to the company’s MyVoice program, which collects and houses a great deal of personal information about each customer. This data can then be fed back into subsequent email campaigns.

Pre-flight emails achieve an average unique open rate of 69% and an average unique click rate of 38%, which is apparently well above industry averages. 

The post-arrival emails have an average unique open rate of 62% and an average unique click rate of 40%.

BustedTee increases revenue 8% with personalised send times

Ecommerce retailer BustedTees has a global customer base however it used to send all of its emails at the same time of day.

Working with a vendor the company segmented its email list by time zone then set its campaigns to be delivered at 10am local time.

However BustedTees then also added an extra layer of segmentation by using past data on individual open times to develop a personalised send time for each subscriber.

The results were as follows:

  • 8% lift in email revenue overnight from personalised send time.
  • 17% increase in total email response rate.
  • 11% higher clickthrough rate.
  • 7.6% increase in post-click site engagement.

Clothing retailer improves open rate by 40%

After finding its email marketing efforts had plateaued multichannel retailer SwayChic implemented a segmentation strategy to increase traffic and maximise revenue from existing customers.

It used historic data to test 30 to 50 different attributes, including days with the highest open rates, time of day, customers’ past purchases, clickthrough rates and time of actual conversions.

New email campaigns were then created which divided customers into different time slots as well as customizing the emails based on their purchase behaviour (e.g. one-time buyer, frequent or lapsed customers).

Overall SwayChic launched 12 optimized email campaigns per month and achieved the following results:

  • Increased average open rate by 40%.
  • Doubled average clickthrough.
  • Tripled revenue for each campaign.

Hotel Chocolat increased website revenue by 12%

Having successfully built up a large email list, Hotel Chocolat was aware that it didn’t want to undo all its hard work by spamming users and causing them to unsubscribe.

It therefore implemented a process of behavioural segmentation, which began by splitting them out based on how they signed up to the email list (i.e. online or in-store).

Separate welcome campaigns were created consisting of four emails that were relevant to the customer’s previous experience with the brand.

Further to this, customer interactions with the brand by email or on-site (e.g. recency and frequency of email opens, frequency of website visits and website purchase activity) are continually fed into a CRM database so they could be targeted with appropriate messages.

Overall and in spite of a 44% increase in Hotel Chocolat’s send volume, the results were as follows:

  • Revenue direct from email increased by 20% helping improve total website revenue by 12%.
  • Average order value increased by 22%.
  • Deliverability improved.
  • Both open rates and click rates increased.
  • There was no negative impact on unsubscribe rates.

Onward Reserve

Ecommerce retailer Onward Reserve moved from a ‘batch and blast’ strategy to a segmented method that used four variations based on customer type: best customers, non-purchasers, churning customers and other.

The groups were sent the same basic template but with different messages tailored to their previous on-site behaviour.

Onward Reserve ran two tests, segmenting a Father’s Day campaign email and an edition of its newsletter called The Gazette.

This chart shows the average improvements that segmentation achieved:

Intermix increased annual revenue by 15%

Women’s retailer Intermix successfully used segmentation to decrease the value of the discounts it was providing in its emails and increase the average revenue per order from email marketing.

Customers were first divided into three segments based on past purchase behaviour, open and click rates and average order values.

These were:

  • VIPs – customers with higher disposable incomes that liked to shop for the latest trends.
  • Sale shoppers – shoppers that were motivated by discounts.
  • Brand shoppers – customers that showed loyalty to particular brands. Though they are price conscious they are also motivated by other factors.

Using these three segments Intermix was able to dynamically adjust its email offers to make them relevant to the recipient.

For example, VIPs received non-monetary offers such as invites to exclusive events or to meet the designers, while sale and brand shoppers received discounts ranging from 30% off and 10-15% respectively.

After an initial testing phase among a small sample Intermix’s conversion rate increased tenfold to around 8%, however it expected that to fall back to around 4% when the segments were implemented among its full list of more than 100,000 customers.

This would still equate to a 15% increase in its annual revenue.